The development of a new drug or medical device can be a challenging and time consuming process. If preclinical testing suggests that a promising compound might be well tolerated in humans, it may be tested for safety and pharmacokinetics (drug absorption and metabolism) in healthy volunteers (Phase I). If the results of Phase I trials warrant further investigation, a limited number of patients with the target disease may be challenged with the drug under carefully controlled conditions to evaluate its efficacy and further establish safety and proper dosages (Phase II). If these trials are successful, the drug enters large-scale trials to better characterize its safety and efficacy in patients (Phase III). Typically, clinical trials are coordinated by either contract research organizations (CROs) or academic medical centers that are sponsored by the pharmaceutical manufacturer. Physicians at these institutions conduct the clinical trials and care for the patients/subjects. The Food and Drug Administration (FDA) is the regulatory body having oversight of drug development, which encompasses the preclinical and clinical trial phases of the new drug discovery and testing in humans.
A significant portion of the time and expense of conducting clinical trials arises from the need to assure that the resulting data is accurate. Patients are selected, treated, and evaluated by a meticulous protocol, and the results are usually recorded on standardized forms (case report forms or CRFs) that are collected and analyzed by the sponsor or its designee. To ensure the validity and accuracy of the data, the pharmaceutical company periodically sends a monitor to study sites to verify that patients are treated according to the study protocol and that the information is reported according to the study protocol. Monitoring alone can represent up to 30 percent of the costs of a clinical trial. Most pharmaceutical companies also have separate quality assurance departments to review forms and audit data and safety departments to monitor and prepare reports on adverse events.
From the pharmaceutical manufacturer's perspective, the key issues with respect to data quality and integrity may include how to accurately collect the information that is necessary to assess the safety and effectiveness of the experimental therapy, as well as how to ensure the quality and integrity of that information, while controlling costs and reducing the time consumed by the clinical trial process. From the FDA's perspective, however, the key issue is ensuring that data submitted in support of an application is a valid representation of the clinical trial, especially as the data pertains to drug safety, pharmacokinetics, and efficacy.
Under the Federal Food, Drug, and Cosmetic Act, pharmaceutical manufacturers must obtain a research or marketing permit before beginning studies on certain commodities such as new human drugs, medical devices, veterinary drugs, and food additives. FDA approves these permits, and also regulates biomedical research whose results are then submitted in support of an application for such a permit. The FDA has two principle objectives in regulating this research: 1) to protect the rights and welfare of human research subjects, and 2) to assure the quality and integrity of the biomedical research data used to support the initiation or expansion of clinical trials, the approval of new products and indications, and the labeling of these products.
Pharmaceutical companies monitor and audit clinical trial data: 1) to ensure the safety of the human subjects, 2) to ensure that the company's investment results in a marketable product, and 3) because it is required by the FDA as follows:                Sponsors are responsible for selecting qualified investigators, providing them with the information they need to conduct an investigation properly, ensuring proper monitoring of the investigation(s), ensuring that the investigation(s) is conducted in accordance with the general investigational plan and protocols contained in the IND (Investigational New Drug application), maintaining an effective IND with respect to the investigations, and ensuring that FDA and all participating investigators are promptly informed of significant new adverse effects or risks with respect to the drug . . . 21 C.F.R. 31.250.        
Although each company may structure its activities in different ways, responsibility for monitoring is typically distributed as follows. The clinical research department includes medical monitors, often physicians with a considerable amount of clinical experience. The greater burden of monitoring falls to the clinical research associates, who go into the field to make sure that sites are properly initiated and the data are collected appropriately. Most companies also have a separate clinical quality assurance department that conducts in-house file audits to ensure that protocols are written correctly, and conducts site and investigator audits to confirm the qualifications of the investigator, to match case report forms with patient charts, and to review the informed consent forms. Members of the biostatistics and data management group, which is usually separate from the clinical research group, monitor all the data received from the field and investigate emerging trends that might affect safety. The drug safety department collects data on serious adverse effects. Finally, the regulatory affairs group compiles expedited serious adverse effects reports and sends them to the appropriate regulatory agencies.
This process generates an enormous volume of data, and the greater the amount of data that is collected the higher the probability of error. The subsequent task of reconciling the various data streams becomes more difficult.
The reality in clinical drug development is that a clinical trial is only as good as the quality of the data. Under current standards of practice, some of which are regulated, “monitoring” represents an ability to assess study progress but not the quality of the data. The pharmaceutical industry's concept of data quality relates to data entry issues rather than the intrinsic value of the data, i.e., generating experimental results that meet the objectives of the trial. This represents a major drawback in how clinical trials are managed, given time sensitive issues (e.g., patent life) and financial issues (cost of development and recovery of the investment with product launch) that drive this effort. Refocusing the clinical trial development effort to prospectively evaluate the quality of the data without biasing the outcome would provide both time and cost savings.
The protocol of a clinical trial represents a complicated roadmap for trial study. Some studies are of a sufficiently long duration such that they may take months to years to complete. The data that is generated for each of the multiple interaction points in a complicated protocol is fundamental to the successful completion of a clinical trial. The definition of a successful study is one that fulfills the experimental objectives of the protocol, i.e., accurately portrays the safety and efficacy of a new drug or medical device (or the lack thereof). Although the clinical trial protocol may have clear experimental objectives, it is the execution of the protocol which can be variable. Late phase studies or pivotal studies (e.g., Phase 3) can often require 500 to 10,000 study subjects, depending on the indication, to demonstrate safety and efficacy. Generally, this requires multiple investigators and/or study sites to enroll and complete this large number of subjects. In general, the FDA requires that a sponsor of a drug successfully complete two pivotal trials of sufficient magnitude to demonstrate safety and efficacy. As one can imagine, given the challenges of studies of this size, there may be a great variation of interpretation in how study subjects are entered and “complete” the protocol. These discrepancies lead to the generation of data of poor quality and universally delay all clinical drug development programs.
Typically, as a clinical trial goes forward, subject data is collected from a primary source, such as a patient's chart, and transferred to case report forms or other subject data receptacle. At this point, mandated monitoring normally takes place, and upon study subject and/or study completion, the data is entered into a database or other data storage area. In current practice, no attempt is made to assess the value or quality of the collected information until the data is entered into the database alongside various predetermined acceptable ranges for each data variable. Data that is outside the range for each variable may trigger a “data query” to the respective study site for purposes of resolution. If there are enough data queries for a subject that cannot be appropriately resolved, the subject may be invalidated and the subject's data may not be used in the study. Depending on the overall study design, subjects that are invalidated often need to be replaced to meet sample size requirements. This failure to proactively assess data quality while the study is in progress results in budget and timeline deviations because additional subjects need to be obtained and their data collected and analyzed.
These and other problems exist.